Weakly supervised object detectors tend to learn only the most discriminative features in images[1]}, [2]}, which will cause network localization errors and decrease detection accuracy. In order to solve this problem, we try to dropout elements in the dimensions of channel and space respectively, as shown in Figure REF .
